latinsquare {languageR} | R Documentation |
Simulated lexical decision latencies with SOA as treatment, using a Latin Square design with subjects and items, as available in Raaijmakers et al. (1999).
data(latinsquare)
A data frame with 144 observations on the following 6 variables.
Group
G1
, G2
and
G3
, for groups of subjectsSubject
S1
, ... S12
.Word
W1
... W12
.RT
SOA
long
, medium
,
and short
.List
L1
, L2
, and L3
for lists of words.Raaijmakers, J.G.W., Schrijnemakers, J.M.C. & Gremmen, F. (1999) How to deal with "The language as fixed effect fallacy": common misconceptions and alternative solutions, Journal of Memory and Language, 41, 416-426.
## Not run: data(latinsquare) library(lme4) latinsquare.with = simulate.latinsquare.fnc(latinsquare, nruns = 1000, with = TRUE) latinsquare.without = simulate.latinsquare.fnc(latinsquare, nruns = 1000, with = FALSE) latinsquare.with$alpha05 latinsquare.without$alpha05 ## End(Not run)